POS8-1037
Engineering Multivalent GalNAc-Conjugated Lipid Nanoparticles for High-Efficiency Liver Targeting
Topic
S8. Frontiers of Functional Polymers in Biology and Medicine
When and Where
Sep 30, 2026
08:30 - 09:30
Room 301 (Grand Ballroom)
Session Chairs
Heesuk KIM
Jinhye BAE
Presenter(s)
Ji Yoon Lee (Korea Research Institute of Bioscience and Biotechnology)
Co-Author(s)
Abstract
Lipid nanoparticles (LNPs) are clinically validated nonviral delivery systems for mRNA therapeutics and vaccines. However, achieving tissue- or cell-specific delivery of LNPs remains a major challenge. Although intravenously administered LNPs predominantly accumulate in the liver through adsorption of circulating apolipoprotein E (apoE) and subsequent low-density lipoprotein receptor (LDLR)-mediated uptake, attachment of N-acetylgalactosamine (GalNAc)—a ligand for the asialoglycoprotein receptor (ASGPR) highly expressed on hepatocytes—to the LNP surface may enable precise and efficient liver targeting while reducing the required dose and potential toxicity. Despite previous studies incorporating GalNAc onto nanoparticle surfaces, systematic investigations of the structure–activity relationships governing liver-targeting efficiency remain limited. Here, we synthesized a series of GalNAc-conjugated poly(ethylene glycol) (PEG)-lipids with varying ligand valencies, linker architectures, and hydrophobic tail structures, and optimized LNP formulations by modulating GalNAc valency and surface density. The resulting LNPs were evaluated for liver-targeting efficiency in vitro and in vivo, together with their safety profiles. GalNAc-conjugated LNPs exhibited markedly enhanced liver-targeting efficiency compared with unmodified LNPs, with delivery performance strongly influenced by PEG-lipid structure. Our findings demonstrate the importance of controlling ligand valency and surface density to maximize multivalent receptor-ligand interactions and provide a rational design strategy for the development of highly efficient liver-targeted LNPs.













